[Method Development] Predicting and Characterizing Alzheimer's Disease & Related Dementias

[analysis] Compressive and reductive analysis of genomic and proteomics data

[method-development] HPC Engine for Mass Spectrometry based Omics Data

[dataset] MLSPred-Bench: Reference EEG Benchmark for Prediction of Epileptic Seizures

[Method Development] Predicting Epileptic Seizures

[Method Development] ML Ecosystem for Mass Spectrometry Data

[Method Development] Characterization and diagnosis of Autism Spectrum

Overcoming Site Variability in Multisite fMRI Studies: An Autoencoder Framework for Enhanced Generalizability of Machine Learning Models

MLSPred-Bench: Transforming Electroencephalography (EEG) Datasets into Machine Learning-Ready Seizure Prediction Benchmarks

Machine-learning models for Alzheimer’s disease diagnosis using neuroimaging data: survey, reproducibility, and generalizability evaluation

TA‐RNN: an Attention‐based Time‐aware Recurrent Neural Network Architecture to Predict Progression of Alzheimer’s Disease

Alzheimer’s disease-associated gene ranking using PhenoGeneRanker

Alzheimer’s disease diagnosis using gray matter of T1-weighted sMRI data and vision transformer

Predicting Individual’s Cognitive Performance Through Multi-Omics Blood Data Using Hierarchical Input Neural Network - HINN

Robustness of ML-Based Seizure Prediction Using Noisy EEG Data From Limited Channels

Lightweight Transformer exhibits comparable performance to LLMs for Seizure Prediction: A case for light-weight models for EEG data

Utilizing Pretrained Vision Transfomers and Large Language Models for Epileptic Seizure Prediction

Predicting peptide properties from mass spectrometry data using deep attention-based multitask network and uncertainty quantification

PVTAD: Alzheimer’s Disease Diagnosis Using Pyramid Vision Transformer Applied to White Matter of T1-Weighted Structural MRI Data

Making MS Omics Data ML-Ready: SpeCollate Protocols

Heterogeneity Aware Distributed Machine Learning at the Wireless Edge for Health IoT Applications: An EEG Data Case Study

Communication Evaluation of a Wireless 4-Channel Wearable EEG for Brain-Computer Interface (BCI) and Healthcare Applications

Systems and methods for matching mass spectrometry data with a peptide database

Statistical and Machine Learning Analysis of the Human Brain Functional Network in a Multi-Site Resting-State Functional MRI Database Framework

Q-CASA Invited Speakers Quantum-Centric Supercomputing Strategies for Neuroscience problems: Challenges and Progress

PPAD: a deep learning architecture to predict progression of Alzheimer’s disease

High Performance Computing Algorithms for Accelerating Peptide Identification from Mass-Spectrometry Data Using Heterogeneous Supercomputers

GPU-acceleration of the distributed-memory database peptide search of mass spectrometry data

Energy Efficient AI/ML based Continuous Monitoring at the Edge: ECG and EEG Case Study

Description of Dissolved Organic Matter Transformational Networks at the Molecular Level

Confounding Effects on the Performance of Machine Learning Analysis of Static Functional Connectivity Computed from rs-fMRI Multi-site Data

ASD-GResTM: Deep Learning Framework for ASD classification using Gramian Angular Field

22nd IEEE International Workshop on High Performance Computational Biology (HiCOMB 2023)

Unsupervised structural classification of dissolved organic matter based on fragmentation pathways

Systems and methods for peptide identification

Systems and methods for measuring similarity between mass spectra and peptides

Systems And Methods For Diagnosing Autism Spectrum Disorder Using fMRI Data

SPERTL: Epileptic Seizure Prediction using EEG with ResNets and Transfer Learning

Re-configurable Hardware for Computational Proteomics

Need for High-Performance Computing for MS-Based Omics Data Analysis

Molecular level characterization of DOM along a freshwater-to-estuarine coastal gradient in the Florida Everglades

Machine-Learning and the Future of HPC for MS-Based Omics

Introduction to Mass Spectrometry Data

High-Performance Computing Strategy Using Distributed-Memory Supercomputers

High-Performance Algorithms for Mass Spectrometry-Based Omics

G-MSR: A GPU-Based Dimensionality Reduction Algorithm

Fast Spectral Pre-processing for Big MS Data

Existing HPC Methods and the Communication Lower Bounds for Distributed-Memory Computations for Mass Spectrometry-Based Omics Data

Computational CPU-GPU Template for Pre-processing of Floating-Point MS Data

Communication lower-bounds for distributed-memory computations for mass spectrometry based omics data

Classification of Autism Spectrum Disorder Using rs-fMRI data and Graph Convolutional Networks

Biomedical IoT: Enabling Technologies, Architectural Elements, Challenges, and Future Directions

A Easy to Use Generalized Template to Support Development of GPU Algorithms

TurboBFS: GPU Based Breadth-First Search (BFS) Algorithms in the Language of Linear Algebra

TurboBC: A Memory Efficient and Scalable GPU Based Betweenness Centrality Algorithm in the Language of Linear Algebra

SpeCollate: Deep cross-modal similarity network for mass spectrometry data based peptide deductions

Source data: high performance computing framework for tera-scale database search of mass spectrometry data

Simulation Testbed for Evaluating Distributed Querying and Searching of Mass Spectrometry Big Data in a Network-based Infrastructure

Search feasibility in distributed MS-proteomics big data

Real-time peptide identification from high-throughput mass-spectrometry data

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey

Machine Learning methods for diagnosing Autism Spectrum Disorder and Attention-deficit/Hyperactivity Disorder using functional and structural MRI: A Survey

High performance computing framework for tera-scale database search of mass spectrometry data

HiCOPS: High Performance Computing Framework for Tera-Scale Database Search of Mass Spectrometry based Omics Data

Graph Theoretic Approach for the Analysis of Comprehensive Mass-Spectrometry (MS/MS) Data of Dissolved Organic Matter

Explainable and scalable machine learning algorithms for detection of autism spectrum disorder using fMRI data

DeepCOVIDNet: Deep Convolutional Neural Network for COVID-19 Detection from Chest Radiographic Images

Communication-avoiding micro-architecture to compute Xcorr scores for peptide identification

Benchmarking mass spectrometry based proteomics algorithms using a simulated database

ASD-SAENet: a sparse autoencoder, and deep-neural network model for detecting autism spectrum disorder (ASD) using fMRI data

A Multi-Factorial Assessment of Functional Human Autistic Spectrum Brain Network Analysis

ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data

NGS-Integrator: An efficient tool for combining multiple NGS data tracks using minimum Bayes’ factors

Methods and systems for compressing data

Federated learning: A survey on enabling technologies, protocols, and applications

Slm-transform: A method for memory-efficient indexing of spectra for database search in lc-ms/ms proteomics

Optimized CNN-based diagnosis system to detect the pneumonia from chest radiographs

NGS‐Integrator: A Tool for Combining Information from Multiple Genome‐Wide NGS Data Tracks Using Minimum Bayes Factors

LBE: A Computational Load Balancing Algorithm for Speeding up Parallel Peptide Search in Mass-Spectrometry based Proteomics

GPU-SFFT: A GPU based parallel algorithm for computing the Sparse Fast Fourier Transform (SFFT) of k-sparse signals

GPU-DFC: A GPU-based parallel algorithm for computing dynamic-functional connectivity of big fMRI data

Efficient shared peak counting in database peptide search using compact data structure for fragment-ion index

Auto-ASD-Network: A technique based on Deep Learning and Support Vector Machines for diagnosing Autism Spectrum Disorder using fMRI data

ASD-DiagNet: A hybrid learning approach for detection of Autism Spectrum Disorder using fMRI data

2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

Towards quantifying psychiatric diagnosis using machine learning algorithms and big fMRI data

Similarity based classification of ADHD using Singular Value Decomposition

Parallel sampling-pipeline for indefinite stream of heterogeneous graphs using OpenCL for FPGAs

MaSS‐Simulator: A Highly Configurable Simulator for Generating MS/MS Datasets for Benchmarking of Proteomics Algorithms

GPU-DAEMON: GPU algorithm design, data management & optimization template for array based big omics data

Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson’s Correlation Coefficients for Time Series Data - An fMRI Study

A Fourier-Based Data Minimization Algorithm for Fast and Secure Transfer of Big Genomic Datasets

A deep learning-based data minimization algorithm for fast and secure transfer of big genomic datasets

Scalable data structure to compress next-generation sequencing files and its application to compressive genomics

Power-Efficient and Highly Scalable Parallel Graph Sampling using FPGAs

GPU-PCC: A GPU Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Big fMRI Data

An out-of-core gpu based dimensionality reduction algorithm for big mass spectrometry data and its application in bottom-up proteomics

A new cryptography algorithm to protect cloud-based healthcare services

A Hybrid MPI-OpenMP Strategy to Speedup the Compression of Big Next-Generation Sequencing Datasets

Systems-level analysis reveals selective regulation of Aqp2 gene expression by vasopressin

Reductive Analytics on Big MS Data leads to tremendous reduction in time for peptide deduction

MS-REDUCE: an ultrafast technique for reduction of big mass spectrometry data for high-throughput processing

Introduction to the selected papers from the 7th International Conference on Bioinformatics and Computational Biology (BICoB 2015)

GPU-ArraySort: A parallel, in-place algorithm for sorting large number of arrays

Data Aware Communication for Energy Harvesting Sensor Networks

A variable-length network encoding protocol for big genomic data

A Parallel Peptide Indexer and Decoy Generator for Crux Tide using OpenMP

On the sampling of big mass spectrometry data

Design and implementation of network transfer protocol for big genomic data

Big data proteogenomics and high performance computing: Challenges and opportunities

Autophagic degradation of aquaporin-2 is an early event in hypokalemia-induced nephrogenic diabetes insipidus

A parallel algorithm for compression of big next-generation sequencing datasets

Global analysis of the effects of the V2 receptor antagonist satavaptan on protein phosphorylation in collecting duct

Foreword to the special issue on selected papers from the 6th International Conference on Bioinformatics and Computational Biology (BICoB 2014).

Exploiting thread-level and instruction-level parallelism to cluster mass spectrometry data using multicore architectures

Cams-rs: clustering algorithm for large-scale mass spectrometry data using restricted search space and intelligent random sampling

A knowledge base of vasopressin actions in the kidney

6th International Conference on Bioinformatics and Computational Biology (BICoB 2014)

Quantitative phosphoproteomics implicates clusters of proteins involved in cell‐cell adhesion and transcriptional regulation in the vasopressin signaling network

Proteome-wide measurement of protein half-lives and translation rates in vasopressin-sensitive collecting duct cells

PhosSA: Fast and accurate phosphorylation site assignment algorithm for mass spectrometry data

Foreword to the special issue on selected papers from the 5th International Conference on Bioinformatics and Computational Biology (BICoB 2013)

A high performance algorithm for clustering of large-scale protein mass spectrometry data using multi-core architectures

A Graphical User Interface (GUI) for Phosphorylation Site Assignment of Protein Mass Spectrometry Data

Quantitative phosphoproteomics in nuclei of vasopressin-sensitive renal collecting duct cells

Proteomic and Metabolomic Approaches to Cell Physiology and Pathophysiology: Quantitative phosphoproteomics in nuclei of vasopressin-sensitive renal collecting duct cells

NHLBI-AbDesigner: an online tool for design of peptide-directed antibodies

Identifying protein kinase target preferences using mass spectrometry

High performance phosphorylation site assignment algorithm for mass spectrometry data using multicore systems

Dynamics of the G protein-coupled vasopressin V2 receptor signaling network revealed by quantitative phosphoproteomics

CP hos: a program to calculate and visualize evolutionarily conserved functional phosphorylation sites

An efficient dynamic programming algorithm for phosphorylation site assignment of large-scale mass spectrometry data

An efficient algorithm for clustering of large-scale mass spectrometry data

A high performance multiple sequence alignment system for pyrosequencing reads from multiple reference genomes

Mining temporal patterns from iTRAQ mass spectrometry (LC-MS/MS) data

Mapping‐based temporal pattern mining algorithm (MTPMA) identifies unique clusters of phosphopeptides regulated by vasopressin in collecting duct

Large‐scale iTRAQ‐based quantification of phosphorylation changes during vasopressin signaling

Parallel Algorithm for Center Star Sequence and Alignments with Applications to Short Reads

High performance computational biology algorithms

A graph-theoretic framework for efficient computation of HMM based motif finder

Pyro-align: Sample-align based multiple alignment system for pyrosequencing reads of large number

Multiple sequence alignment system for pyrosequencing reads

An Overview of Multiple Sequence Alignment Systems

A domain decomposition strategy for alignment of multiple biological sequences on multiprocessor platforms

Sample-align-d: A high performance multiple sequence alignment system using phylogenetic sampling and domain decomposition

NIH Funding Mechanisms (Research and Development) - DP grants - part 2

NIH Funding Mechanisms (Research and Development) - part 1

Informal blog for better scientific communication